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Practical Time Series Analysis

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Track :

Programming

Lessons no : 5

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What will you learn in this course?
  • Develop skills to preprocess and visualize time series data for accurate analysis and insights using Python and R tools
  • Apply statistical models like ARIMA, SARIMA, and Exponential Smoothing to forecast economic, financial, and sales data accurately
  • Identify and interpret patterns such as trends, seasonality, and anomalies in time series datasets for informed decision-making
  • Implement practical techniques for stationarity testing, differencing, and model validation to enhance forecasting reliability

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Lessons | 5


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4.5
2 Reviews
Kumneger Taye 

VERY NICE
2025-06-07

C. Sai venkat girish 

Good
2024-11-15

MD SHAHID RAJA 

mind  boaling to good
2024-11-08

Sriranjani Statistics 

Courses are excellent with examples
2024-04-05

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Time series analysis is extremely useful to observe how a given asset, security, or economic variable behaves/changes over time. For example, it can be deployed to evaluate how the underlying changes associated with some data observation behave after shifting to other data observations in the same time period .